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Modern Portfolio Theory explores how risk averse investors construct portfolios in order to optimize market risk against expected returns. The theory quantifies the benefits of diversification.Modern Portfolio Theory provides a broad context for understanding the interactions of systematic risk and reward. It has profoundly shaped how institutional portfolios are managed, and has motivated the use of passive investment management techniques, and the mathematics of MPT is used extensively in financial risk management.Advances in Portfolio Construction and Implementation offers practical guidance in addition to the theory, and is therefore ideal for Risk Mangers, Actuaries, Investment Managers, and Consultants worldwide. Issues are covered from a global perspective and all the recent developments of financial risk management are presented. Although not designed as an academic text, it should be useful to graduate students in finance.
List of contents
A review of portfolio planning: models and systems; Generalised mean variance analysis and robust portfolio diversification; Portfolio construction from mandate to stock weight: a practitioner's perspective; Enhanced indexation; Portfolio management under taxes; Using genetic algorithms to construct portfolios; Near-uniformly distributed, stochastically generated portfolios; Modelling directional hedge funds mean, variance and correlation with tracker funds; Integrating market and credit risk in fixed income portfolios; Incorporating skewness and kurtosis in portfolio optimization: a multidimensional efficient set; Balancing growth and shortfall probability in continuous time active portfolio management; Assessing the merits of risk-based optimisation for portfolio concentration; The mean-downside risk portfolio frontier: a non-parametric approach ; Some exact results for portfolio estimators in the two-period capital market model; optimal asset allocation for endowments: a large deviations approach; Methods of relative portfolio optimization; Predicting portfolio returns using exact efficient set distributors
